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New high-throughput search strategies based on statistical identification of promising chemical subspaces show potential for accelerating half-Heusler thermoelectric materials discovery. 

Abstract Superionic conductors, includingACrX₂(A=Ag, Cu; X = S, Se) compounds, have attracted attention due to their low lattice thermal conductivity and high ionic conductivity. These properties are driven by structural characteristics such as anharmonicity, soft bonding, and disorder, which enhance both fast ion transport and thermal resistance. In the present study, we investigate the impact of various factors (e.g.A-site disorder, microstructure, speed of sound and chemical composition) on the thermal conductivity of the compounds CuCrS₂, CuCrSe₂, AgCrS₂and AgCrSe₂. The samples were synthesized using solid state reaction, ball milling and subsequent spark plasma sintering, and thermal diffusivity, electrical resistivity, Hall coefficients and Seebeck coefficients were measured as a function of temperature. The selenides were found to behave as degenerate semiconductors, with reasonable thermoelectric figure of merit (up to 0.79 in CuCrSe₂), while the sulfides behaved as non-degenerate semiconductors with high electrical resistivity. At room temperature, all samples are in the ordered phase and show low lattice thermal conductivity ranging from 0.60 W m⁻¹-K in AgCrSe₂to 1.1 W m⁻¹-K in CuCrSe₂. Little reduction in lattice thermal conductivity was observed in the high-temperature phase, despite the increased disorder on the cation site and the onset of superionic conductivity. This suggests that the low lattice thermal conductivity inACrX₂compounds is an inherent property of the crystal structure, caused by anharmonic bonding and diffuson dominated transport. 

The solid solution behavior of ZnTe in CuInTe2 complicates defect analysis. 

Bi1−xSbx alloys are classic thermoelectric materials for near-cryogenic applications. Despite more than half a century of study, unraveling the underlying transport physics within this space has been nontrivial due to the complex electronic structure, disorder, and small bandgap within these alloys. Furthermore, as Peltier coolers, Bi1−xSbx alloys operate in a bipolar regime; as such, understanding the impact of minority carriers is critical for further improvements in device performance. This study unites first principles calculations with low-temperature experimental measurements to create a generalized model for transport within semiconducting Bi-Sb alloys. Our exploration reveals the interplay between the complex, degenerate valence band structure with the extremely light conduction bands. By building a hybrid computational/experimental model, an understanding of both the electron and hole relaxation times emerges both as a function of temperature and energy. Special quasi-random supercell calculations reveal that, despite significant atomic disorder, the electronic band structures within the alloy remains largely unaffected and electron–phonon scattering dominates. For charge carriers near the band edges, the relaxation times are thus extremely long, consistent with cyclotronic behavior appearing at low magnetic fields (≪ 1 T). Modeling thermoelectric performance suggests that the valence band edge deformation potential is significantly weaker and highlights the potential for p-type compositions to meet or exceed the current n-type alloys. 

Abstract Data-driven approaches to materials exploration and discovery are building momentum due to emerging advances in machine learning. However, parsimonious representations of crystals for navigating the vast materials search space remain limited. To address this limitation, we introduce a materials discovery framework that utilizes natural language embeddings from language models as representations of compositional and structural features. The contextual knowledge encoded in these language representations conveys information about material properties and structures, enabling both similarity analysis to recall relevant candidates based on a query material and multi-task learning to share information across related properties. Applying this framework to thermoelectrics, we demonstrate diversified recommendations of prototype crystal structures and identify under-studied material spaces. Validation through first-principles calculations and experiments confirms the potential of the recommended materials as high-performance thermoelectrics. Language-based frameworks offer versatile and adaptable embedding structures for effective materials exploration and discovery, applicable across diverse material systems. 

Successful dopability in AgInTe₂requires careful navigation of the compensating intrinsic defects to maximize dopant solubility and efficiency. 

Germanium telluride is a high performing thermoelectric material that additionally serves as a base for alloys such as GeTe–AgSbTe 2 and GeTe–PbTe. Such performance motivates exploration of other GeTe alloys in order understand the impact of site substitution on electron and phonon transport. In this work, we consider the root causes of the high thermoelectric performance material Ge 1− x Mn x Te. Along this alloy line, the crystal structure, electronic band structure, and electron and phonon scattering all depend heavily on the Mn content. Structural analysis of special quasirandom alloy structures indicate the thermodynamic stability of the rock salt phase over the rhombohedral phase with increased Mn incorporation. Effective band structure calculations indicate band convergence, the emergence of new valence band maxima, and strong smearing at the band edge with increased Mn content in both phases. High temperature measurements on bulk polycrystalline samples show a reduction in hole mobility and a dramatic increase in effective mass with respect to increasing Mn content. In contrast, synthesis as a function of tellurium chemical potential does not significantly impact electronic properties. Thermal conductivity shows a minimum near the rhombohedral to cubic phase transition, while the Mn Ge point defect scattering is weak as indicated by the low K L dependence on the Ge–Mn fraction (Fig. 10). From this work, alloys near this phase transition show optimal performance due to low thermal conductivity, moderate effective mass, and low scattering rates compared to Mn-rich compositions.